Threat Landscape for 6G ‐Enabled Massive IoT

Abstract

Over the past few years, we have witnessed global initiatives that have been focused on shaping the vision and research agenda for 6 th Generation (6G) mobile networks, which are expected to surpass the capabilities of 5 th Generation (5G) mobile networks and adequately support the Internet of Everything (IoE) applications. In particular, it is anticipated that 6G mobile networks will truly meet the stringent network performance requirements of the emerging disruptive massive IoT applications that 5G cannot support due to its inherent limitations. 6G mobile networks, expected to be commercially available from 2030 onwards, are envisioned to support a much broader range of applications compared to 5G by interconnecting hundreds of billions of IoT devices. However, the rapid expansion of 6G-enabled IoT devices and the increasing number of their interconnections will heighten the vulnerabilities of the 6G-enabled massive IoT applications and pose significant security and privacy risks. Therefore, this chapter gives a comprehensive overview of representative massive IoT applications envisioned to be deployed in the 6G era to improve people's lives and identifies the threat landscape of these applications. The aim is to shed light on their potential key threats and identify security and privacy issues that should be addressed before the 6G-enabled massive IoT applications build trust among all relevant stakeholders and realize their full potential.

Authors 7

1. Μαρία Παπαϊωάννου

   University of Greenwich

   Affiliation as printed

   Faculty of Engineering and Science, University of Greenwich, Chatham Maritime, UK

2. Γεώργιος Μαντάς

   Instituto de Telecomunicações · University of Greenwich

   Affiliation as printed

   Faculty of Engineering and Science, University of Greenwich, Chatham Maritime, UK

   Instituto de Telecomunicações, Aveiro, Portugal

3. Firooz B. Saghezchi Aachen Chair for Distributed Signal Processing

   RWTH Aachen University

   Affiliation as printed

   Chair for Distributed Signal Processing, RWTH Aachen University, Aachen, Germany

4. Georgios Kambourakis

   University of the Aegean

   Affiliation as printed

   Department of Information and Communication Systems Engineering, School of Engineering, University of the Aegean, Samos, Greece

5. Felipe Gil‐Castiñeira

   Universidade de Vigo

   Affiliation as printed

   Telematics Engineering Department, University of Vigo, Vigo, Spain

6. Raúl Santos de la Cámara

   HI Iberia (Spain) · Iberia (Spain)

   Affiliation as printed

   R&D Department, HI Iberia Ingenierıa y Proyectos, S.L., Madrid, Spain

7. Jonathan Rodrı́guez

   University of South Wales

   Affiliation as printed

   Faculty of Computing, Engineering and Science, University of South Wales, Pontypridd, UK